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A Voice-Enabled Game Based Learning Application using Amazon's Echo with Alexa Voice Service: A Game Regarding Geographic Facts About Austria and Europe

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An educational, interactive Amazon Alexa Skill called “Österreich und Europa Spiel / Austria and Europe Game” was developed at Graz University of Technology for a German as well as English speaking audience. This Skills intent is to assist learning geographic facts about Austria as well as Europe by interaction via voice controls with the device. The main research question was if an educational, interactive speech assistant application could be made in a way such that both under-age and full age subjects would be able to use it, enjoy the Game Based Learning experience overall and be assisted learning about the Geography of Austria and Europe. The Amazon Alexa Skill was tested for the first time in a class with 16 students at lower secondary school level. Two further tests were done with a total of five adult participants. After the tests the participants opinion was determined via a questionnaire. The evaluation of the tests suggests that the game indeed gives an additional motivational factor in learning Geography.
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PaperA Voice-Enabled Game Based Learning Application using Amazon's Echo with Alexa Voice
A Voice-Enabled Game Based Learning Application
using Amazon's Echo with Alexa Voice Service
A Game Regarding Geographic Facts About Austria and Europe
https://doi.org/10.3991/ijim.v14i03.12311
Leonardo Bilic, Markus Ebner, Martin Ebner ()
Graz University of Technology, Graz, Austria
martin.ebner@tugraz.at
Abstract—An educational, interactive Amazon Alexa Skill called Oster-
reich und Europa Spiel / Austria and Europe Game” was developed at Graz
University of Technology for a German as well as English speaking audience.
This Skills intent is to assist learning geographic facts about Austria as well as
Europe by interaction via voice controls with the device. The main research
question was if an educational, interactive speech assistant application could be
made in a way such that both under-age and full age subjects would be able to
use it, enjoy the Game Based Learning experience overall and be assisted learn-
ing about the Geography of Austria and Europe. The Amazon Alexa Skill was
tested for the first time in a class with 16 students at lower secondary school
level. Two further tests were done with a total of five adult participants. After
the tests the participants opinion was determined via a questionnaire. The eval-
uation of the tests suggests that the game indeed gives an additional motivation-
al factor in learning Geography.
KeywordsGame-based learning experience, geography, educational, interac-
tive, voice enabled, speech assistant, Amazon Alexa
1 Introduction
Through the constant progress in artificial intelligence and especially regarding
voice-enabled services it seems like every day the possibilities for new applications in
regard to speech-controlled systems would increase. Service providers like Amazon’s
Alexa, Apple’s Siri, Microsoft’s Cortana and many more constantly get new updates
and with those new features. Why should we stop at simple controls like asking for a
weather report, making a phone call, buying groceries online or other services such
voice assistants provide at this very moment? This question led to the idea and further
to the development of the “Österreich und Europa Spiel / Austria and Europe Game”.
The motivation was to build a fully speech-controlled game with which the audience
might be able to learn and enjoy the Game based learning experience.
As stated by both Malone and Plato [1] the idea to use games to improve the intrin-
sic motivation of students within the learning process is not new. Malone started al-
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PaperA Voice-Enabled Game Based Learning Application using Amazon's Echo with Alexa Voice
ready in 1980 with his previously mentioned PhD thesis. Today we face different
challenges which legitimate the work on this topic. As Böckle et al. fittingly states
[2]:
“Today’s challenge follows the interests and creativity of an individual student.
One of the most interesting fields in this research is Game Based Learning (GBL),
which is very similar to Problem Based Learning (PBL), where a specific problem
scenario is embedded within a play framework (Barrows & Tamblym, 1980). Despite
the widespread recognition of the advantages of using games in elementary and sec-
ondary education as well as in higher education, little evidence can be found on the
use of digital and/or online games.” [2]
There are not many games which are widely popular known for voice-enabled de-
vices and if there are such they are mostly restricted to a certain age or by only having
one language. It was intended to be multilingual from the beginning and was imple-
mented in German first and English afterwards. First it was intended to have a narrow
target audience regarding age however the final decision was to make it available and
interesting for everyone.
2 The Game
2.1 Concept
At first the Amazon Alexa Skill was analyzed and designed. The game should be
similar to other Trivia, Quizzes and as such an interactive game based learning expe-
rience. Malone states further [1] that there are different types of factors which need to
be fulfilled in order to provide an intrinsically motivating environment. The factors
are:
Challenge: Basically, the challenge within the game can be both extrinsic as well
as intrinsic. A simple comparison between intrinsic and extrinsic motivation would
be a competitive Multiplayer community versus Singleplayer experiences which a
player plays only for his or her own enjoyment.
Fantasy: Malone describes this as the ability of a theme to embody or encourage
using one’s own fantasy.
Curiosity: Novelty, complexity, surprisingness and incongruity are just a few con-
cepts which Malone states here.
Not all aspects were implemented to all user’s satisfaction however, the overall
feedback was rather positive.
Additionally, it has to be mentioned that this should be a Game Based Learning
experience and as such a main goal was to make sure that the user not only plays the
game but also learns about the subject while doing so. It does not matter if the user
answers right or wrong after the question he or she will get additional information on
the asked question. The questions for the game were formed by research in a Geogra-
phy book [6] as well as in an Atlas [5].
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A question that arose during the planning phase was what would legitimate the
game compared to other already existing games and possibly other researches. The
main points are listed below:
Focus on Austria and Europe
Game modes: There are different game modes. See section 2.3 Game modes for
further details.
Visual feedback: Another feature implemented is the possibility to visualize the
audio input and output. Thus the user could experience the game both visually and
audible.
Multilingual experience: One of the most important aspects is that the game is
multilingual and through that more accessible to a broader audience.
Trend on digitalization in education in Austria: As stated in the “Nationaler
Bildungsbericht 2018, Band 2. Fokussierte Analysen und Zukunftsperspektiven für
das Bildungswesen” in the chapter 8 “Bildung im Zeitalter der Digitatlisierung”[4]
more and more primary schools already use computers for E-Learning.
Although one might think that multilingual support might not be of such im-
portance one has simply to look at localisation in commercial video games. As Ber-
nal-Merino states in his book [3] “Translation and Localisation in Video Games”:
“The game publishing industry is slowly realising the crucial part that the localisa-
tion of multimedia interactive entertainment software, a.k.a. game localisation, plays
in boosting sales globally, opening new markets and expanding franchises. Nonethe-
less, some companies (developers and publishers) still seem to be unable to fully
integrate best localisation planning and practices into their workflow, and academics
conducting research in this field are also thin on the ground which does not help to
improve the situation.”
As it gains more demand to be able to use a variety of information and communica-
tion technologies and voice-enabled technologies are due to the fact that they are quite
new a niche market the importance of the project and its research is assured.
2.2 Technical background
The service itself was implemented self-hosted. There is the possibility to imple-
ment applications with the Amazon Web Service (AWS). However the final decision
was to develop the game self-hosted with the Flask-Ask framework as this provided
more freedom overall.
The big picture of how components work with each other can be seen visualized in
figure 1:
The actor gives a voice command to the device. The device can be arbitrary as long
as the Amazon Voice Service can be installed on it. It was tested on Android
smartphones, a Raspberry Pi and the official Amazon Echo (2. Gen.).
The device sends the information gathered to the Amazon Voice Service.
Here the audio gets forwarded to the Endpoint defined within the Amazon Alexa
Skill. This is the start of the HTTPS communication.
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PaperA Voice-Enabled Game Based Learning Application using Amazon's Echo with Alexa Voice
The next step is the Intent Recognition Algorithm.
Amazon’s Server forwards the result then to our server. Then the internal server
logic handles the intent accordingly to the implemented protocol. For example if a
question was asked and the user answered then the internal logic would determine
if the question was right, wrong or if the user said that he or she didn’t know.
The output from the server will be forwarded to the Amazon Voice Service.
Here the output gets transformed from text to audio.
Finally, the device answers the actor on his or her initial command.
Fig. 1. Screenshot of a HTTP Communication during a game execution
As can be seen in figure 1 the third step is a transition from the client’s side to Am-
azon’s server and will be redirected later to our local server. This is done via HTTPS.
Of course, HTTPS is not a perfectly secure way to communicate as it can be hacked
with strategic Man in The Middle Attacks with tools like ARP Spoofing, DNS Spoof-
ing, Sniffing and SSL Dump as Chomsiri states [7].
2.3 Game modes
The initial design intended to have two different modes. The first mode was called
the “Quiz game”. In this game mode the user would get a question and four possible
answers with one of which the user had to choose of, e.g.: How many states has
Austria?” with four possible answers.
The second mode was called “Relations game”. As the name already suggests this
game gave the player two objects in relation to each other and the player had to figure
out on which a certain adjective applied. An example for a question would be Which
lake is bigger?” with two lake options given.
The different game modes satisfy different of Malone’s previously mentioned mo-
tivational factors with different weight.
The questions for the different game modes and their answers were stored in a
XML file, which the server reads upon its setup phase.
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2.4 Evaluation
The game was first tested in a secondary school where two teachers and 16 stu-
dents tested the application. The students were divided in four groups of three stu-
dents and one group of four students. Later three adult subjects tested the game at the
Graz University of Technology. The under-aged subjects tested the German version as
it is their native language. The adults however tested the application in English. A
vocabulary sheet was provided in case some words might be unknown to the testers as
English was not their native language. However, afterwards nobody stated that the
vocabulary was a problem. Nobody was allowed to use the visual assistance provided
by the cards that were implemented. As such the whole test was only perceived via
hearing. Before the actual test started a disclosure was given that none of the names or
the individual results will get published and for the students also that they will not be
graded.
Before the interview every participant was asked the questions he or she had an-
swered wrong again to see if they paid attention to the information given by the de-
vice afterwards. The evaluation had six statements and each had to be answered in a
scale with points from one up to five where five is the highest score of approval and
one the lowest. The groups of students evaluated together and had to discuss internal
which the final score they wanted to give to certain statements was. The adults how-
ever all evaluated individually. The result of the evaluation can be seen in table 1 for
the student groups and in table 2 for the individual adults who participated.
Table 1. The evaluation results from the students
Statement
Group 1
Group 2
Group 3
Group 4
The application was easy to use
5
5
5
5
The game was fun to play
5
4
4
5
I could imagine playing the game in my free time
4
5
3
3
The game’s questions were easy to answer
5
4
3
5
I would like to play the game again
5
4
5
5
I have learned something while playing the game.
3
2
3
4
Table 2. The evaluation results from the adults
Statement
Adult 1
Adult 2
Adult 3
Adult 4
Adult 5
The application was easy to use
5
5
5
4
5
The game was fun to play
4
5
4
4
4
I could imagine playing the game in my free time
4
5
3
2
1
The game’s questions were easy to answer
2
4
4
3
4
I would like to play the game again
4
5
2
3
2
I have learned something while playing the game.
4
5
4
4
3
3 Conclusion and Future Work
After completion of all those milestones many insights were given on what can and
should be done in the future of the project as it is crucial to keep working on the ap-
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PaperA Voice-Enabled Game Based Learning Application using Amazon's Echo with Alexa Voice
plication. One aspect which needs to be tested is if the server is able to operate on
different operating systems as well. This however is not as big as a priority. At a clos-
er look it seems that Amazon itself has some bigger problems with their voice-
enabled devices and services. There are a couple of problems:
Wrong evaluation: As many participants of the evaluation phase commented Am-
azon understood their spoken words wrong although they did speak loud and clear
in a calm environment.
Accelerating speech speed bug: The issue with Amazon suddenly speeding up the
given speech was not reproducible. It occurred on different sentences and some-
times it did not occur at all.
Overall speech speed: One has to mention that it is unfortunate that the speed of
spoken words of Amazon’s Alexa cannot be regulated.
No possibility for interactivity with visual feedback: The cards provided by
Amazon give the user a possibility to both have an audio and visual feedback expe-
rience. However there is left unused potential as it is not possible to interact also
with the visual feedback. An example for using it would be that during the game
the user could look and interact with a map.
Intent recognition: The intents get recognized by Amazon at their server but there
is no way to observe on how this is done which makes it rather difficult to work on
unwanted behavior.
The experience overall regarding the program’s and with that the server’s logic in
Python using the Flask-Ask framework was very pleasant as it provided a simple to
use framework with almost no problems at all. One has to mention however that it is
very unfortunate that one cannot access the language of the device connected. For the
future it would be definitely of interest to implement more different subjects as this
was requested by some external testers. Further should be analyzed if other voice
service providers would be more adequate as Amazon’s Alexa proofed to have a lots
of issues or to use a self-implemented voice-enabled service self which upon the game
would be built on. Another feature which might be interesting is to save the data of
users in a database such that not only the current session is used for the game as this
information is volatile. Amazon’s Alexa does not provide for Skill developers to dif-
ferentiate between persons upon their voices which technically should be possible. It
would also be of interest for the project’s good to test if a combination of both voice
and more classic input technologies like mouse and keyboard would increase the
overall satisfaction of users.
4 Acknowledgement
Special Thanks to the BG/BRG/BORG Köflach, all the children for participating,
their parents and teachers for making this possible and all the other testers who
showed interest and participated.
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5 References
[1] Malone W. Thomas. (1981) “What makes things fun to learn? A study of intrinsically mo-
tivating computer games.” https://doi.org/10.1145/800088.802839
[2] Böckle Martin, Ebner Martin, and Schön Martin. (2007) “Game Based” Learning in Sec-
ondary Education: Geographical Knowledge of Austria.”
[3] Bernal-Merino A. Miguel. (2014) “Translation and localisation in video games: Making
entertainment software global.” Routledge. ISBN: 978-1-3157-5233-4 https://doi.org/10.
4324/9781315752334
[4] Brandhofer Gerhard, Baumgartner Peter, Ebner Martin, Köberer Nina, Trültzsch-Wijnen
Christine, and Wiesner Christian. (2018) “Bildung im Zeitalter der Digitatlisierung.” In:
Nationaler Bildungsbericht Österreich, Band 2. Leykam. ISBN: 978-3-7011-8118-6
[5] Hölzel Eduard. (2015) “Grosser Kozenn-Atlas.” Hölzel. ISBN: 978-3-85116-607-1
[6] Mayrhofer Gerhard, Posch Robert, and Reiter Isabell. (2015) “GEOprofi Geographie und
Wirtschaftskunde für die 5. Schulstufe. Vol. 6” Veritas Verlag. ISBN: 978-3-7058-8415-1
[7] Chomsiri Thawatchai (2007) “HTTPS hacking protection.”https://doi.org/10.
1109/AINAW.2007.200
6 Authors
Leonardo Bilic is an Austrian Computer Science Master’s degree student at the
Graz University of Technology. Besides he works part-time as both a tutor at TU
Graz and as an intern at NXP Semiconductors.
Markus Ebner, is currently working as a Researcher in the Department
Educational Technology at Graz University of Technology. He deals with e-
learning, mobile learning, technology enhanced learning and Open Educational Re-
sources. His focus is on Learning Analytics at K-12 level. In addition, several publica-
tions in the area of Learning Analytics were published and workshops on the topic
were held.
Martin Ebner, is with the Department Educational Technology at Graz University
of Technology, Graz, Austria. As head of the Department, he is responsible for all
university wide e-learning activities. He is an Assoc. Prof. on media informatics and
works at the Institute of Interactive Systems and Data Science as senior researcher.
For publications as well as further research activities, please visit:
http://martinebner.at. Email: martin.ebner@tugraz.at
Article submitted 2019-11-11. Resubmitted 2019-12-11. Final acceptance 2019-12-13. Final version
published as submitted by the authors.
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... Further, learning is supported by Alexa [1], e.g. learning geographic facts [2] and it can be used in mass education [3] as well. ...
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